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Journal of Integrative Bioinformatics

Editor-in-Chief: Schreiber, Falk / Hofestädt, Ralf

Managing Editor: Sommer, Björn

Ed. by Baumbach, Jan / Chen, Ming / Orlov, Yuriy / Allmer, Jens

Editorial Board: Giorgetti, Alejandro / Harrison, Andrew / Kochetov, Aleksey / Krüger, Jens / Ma, Qi / Matsuno, Hiroshi / Mitra, Chanchal K. / Pauling, Josch K. / Rawlings, Chris / Fdez-Riverola, Florentino / Romano, Paolo / Röttger, Richard / Shoshi, Alban / Soares, Siomar de Castro / Taubert, Jan / Tauch, Andreas / Yousef, Malik / Weise, Stephan

4 Issues per year


CiteScore 2017: 0.77

SCImago Journal Rank (SJR) 2017: 0.336

Open Access
Online
ISSN
1613-4516
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Volume 13, Issue 5

Issues

Current Progress of High-Throughput MicroRNA Differential Expression Analysis and Random Forest Gene Selection for Model and Non-Model Systems: an R Implementation

Jing Zhang
  • Institute of Biochemistry and Department of Biology, Carleton University, 1125 Colonel By Drive, K1S 5B6, Ottawa, Ontario, http://carleton.ca/ Canada
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Hanane Hadj-Moussa
  • Institute of Biochemistry and Department of Biology, Carleton University, 1125 Colonel By Drive, K1S 5B6, Ottawa, Ontario, http://carleton.ca/ Canada
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Kenneth B. Storey
  • Corresponding author
  • Institute of Biochemistry and Department of Biology, Carleton University, 1125 Colonel By Drive, K1S 5B6, Ottawa, Ontario, http://carleton.ca/ Canada
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2017-04-20 | DOI: https://doi.org/10.1515/jib-2016-306

Summary

MicroRNAs are short non-coding RNA transcripts that act as master cellular regulators with roles in orchestrating virtually all biological functions. The recent affordability and widespread use of high-throughput microRNA profiling technologies has grown along with the advancement of bioinformatics tools available for analysis of the mounting data flow. While there are many computational resources available for the management of data from genomesequenced animals, researchers are often faced with the challenge of identifying the biological implications of the daunting amount of data generated from these high-throughput technologies. In this article, we review the current state of highthroughput microRNA expression profiling platforms, data analysis processes, and computational tools in the context of comparative molecular physiology. We also present RBioMIR and RBioFS, our R package implementations for differential expression analysis and random forest-based gene selection. Detailed installation guides are available at kenstoreylab.com.

About the article

Published Online: 2017-04-20

Published in Print: 2016-12-01


Citation Information: Journal of Integrative Bioinformatics, Volume 13, Issue 5, Pages 35–46, ISSN (Online) 1613-4516, DOI: https://doi.org/10.1515/jib-2016-306.

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© 2016 The Author(s). Published by Journal of Integrative Bioinformatics.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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